For detecting/recognizing repetitive motions, in particular rhythmic gestures, with at least one motional speed and each at least one repetition in a limited area, in particular of an indoor area, many different approaches (e.g. methods, systems, etc.) exist, but all of them have each pros and cons. A limited area besides the mentioned indoor area but outside of a building is for example a radio range, whereby the limitation is given by the radio coverage.
There are many examples of methods for detecting/recognizing repetitive motions, in particular rhythmic gestures, used in products on the market today. However they all have drawbacks that make them ill-suited for use as part of a modern home automation system. The vast majority of solutions fit into one of two general categories:                Camera-based solutions and        Hardware controller-based solutions.        
Both of these categories have the same problem that they require additional hardware to function. This means that they do not fulfill the requirement of maintaining low cost and simplicity.
Hardware controllers, such as a remote control fitted with a gyroscope, also have the obvious problem that they require the user to carry a physical device. This defeats a lot of the purpose of having a gesture recognition system in the first place since the user could simply push a button on the remote instead.
Camera-based gesture recognition, while avoiding the problem of requiring the user to carry an additional device, does not sufficiently satisfy the point of respecting the user's privacy. MICROSOFT KINECT is an example of a camera-based gesture recognition device. MICROSOFT was met with serious criticism when it announced it would require the KINECT for the XBOX ONE to always be on in order for the console to work. This policy was especially unpopular in countries like Germany and Australia and MICROSOFT eventually reversed its policy. Due to the nature of a home automation implementation, it would be difficult to avoid an always-on solution.
Besides the previous mentioned conventional approaches there are a few new technologies that take advantage of the ubiquitous presence of wireless communication networks in modern homes and buildings. Specifically, these include the projects “WiSee” and “AllSee” from the University of Washington. Both of these projects have the problem that they require non-standard or proprietary hardware. “AllSee” has a significant custom hardware component and “WiSee” uses an expensive software defined radio and many antennas. Thus, neither qualifies as using off-the-shelf hardware.
Yet another similar project is “Wi-Vi” from the Massachusetts Institute of Technology, which also uses multi-antenna hardware with special antenna separation for sending and receiving simultaneously through complicated software defined radio hardware to achieve the gesture recognition.
A further project which claims to see through walls using “Wi-Fi” has been developed by the University of California, Santa Barbara, which uses laser scanners, specially calibrated tires, for centimeter-millimeter controlled movement of synchronized robots and specially directed high-gain antennas to obtain the signal. This is a complicated solution, which uses robots instead of the simple off-the-shelf wireless hardware.
Other approaches may exist. But none of the currently fulfill the following requirements raised out of the above reflection of the different approaches:                Fast acting,        Covering the limited area (e.g. a radio range), in particular the whole apartment,        People carrying no devices        Off-the-shelf hardware and        Single-Sensor.        